Results 281 to 290 of about 66,774 (311)

A Research on the Improvement of Dual Optimization on BP Neural Network

2017 13th International Conference on Computational Intelligence and Security (CIS), 2017
At present, the most widely used BP network model in traffic, agriculture and related data mining is still an important neural network algorithm model, but its performance has not been satisfactory. The convergence and prediction accuracy of the BP neural network is general and easy to fall into the local optimal solution, and these shortcomings still ...
Ruliang Wang, Yang Xuan
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Realization and Discussion of BP Neural Network based on C++

The 2nd International Conference on Computing and Data Science, 2021
Artificial neural network is a large-scale and highly parallel intelligent information processing system, which is inspired by human neural system and is widely connected by multiple neurons. In recent years, the theory and application of artificial neural network have penetrated into various fields, and achieved success in intelligent control, pattern
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Coal Requirement Prediction Using BP Neural Network

2010 International Conference on E-Business and E-Government, 2010
Coal is one of the most important main energy-consuming resources in our society. It is important to forecast the coal requirement with high accuracy. BP neural network forecasting model has the typical of self-learning and self-adaptation. It is often used in these systems that are difficult to create accurate mathematical model.
Xu Xin, Xuli Hong
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BP-Neural Network for Business Administration

2021
With the further deepening of education reform in our country, it has become an important task to adopt new teaching methods to cultivate talents needed by the market. In order to effectively improve the effect of business administration teaching, teachers should actively explore the importance and practical application process of applying simulation ...
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Integration of TACO and BP Neural Network

2008 International Symposium on Intelligent Information Technology Application Workshops, 2008
As one of the extensive applications of artificial neural network, BP algorithm has some shortcomings such as local optimum. In this paper, we propose a new method--TACO-BP algorithm to train neural network, which may overcome the shortcoming. Firstly, we give description about the TACO-BP.
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Hybrid BP/CNN neural network for intrusion detection

Proceedings of the 3rd international conference on Information security, 2004
In order to improve the intrusion detection rates and reduce false positives, a hybrid BP/CNN neural network is constructed, which has both the capability of real-time classification which BP has and the functionality of time-delay, collection and judgment which chaotic neuron has.
Yu Yao 0002, Fuxiang Gao, Ge Yu 0001
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An APSO optimized BP neural network

2011 International Conference on Electronics, Communications and Control (ICECC), 2011
In this paper, the limitations of conventional BP algorithm was analyzed, and to fasten the learning velocity of neural network and enhance its generalization capability, the APSO (adaptive particle swarm optimization) algorithm was introduced into BP network for the optimization of its weights and thresholds.
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Research on the Application of the BP Neural Network

Applied Mechanics and Materials, 2014
The paper constructs an evaluation model for practical teaching quality based on Back Propagation (BP) neural network. It makes the indicators of evaluating practical teaching quality as input data, while practical teaching quality as output results.
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BP NEURAL NETWORK-BASED EFFECTIVE FAULT LOCALIZATION

International Journal of Software Engineering and Knowledge Engineering, 2009
In program debugging, fault localization identifies the exact locations of program faults. Finding these faults using an ad-hoc approach or based only on programmers' intuitive guesswork can be very time consuming. A better way is to use a well-justified method, supported by case studies for its effectiveness, to automatically identify and prioritize ...
W. Eric Wong, Yu Qi
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A Novel Algorithm on BP-Neural Network

2012 International Conference on Computer Science and Electronics Engineering, 2012
Because during the net work learning, BP fall into local minimum, this article proposed a prove algorithm that change the learning gradient, and adjust the weight and threshold, in order to speed up the network's learning speed. At last, this method was used to, study sample at the fuzzy reasoning layer by BP calculation method, obtain professional ...
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